North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube)
The Meteosat Second Generation (MSG) geostationary platform equipped with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument provides observations of the Earth every 15 min since 2004. Based on those measurements, we present a new method called North African Sandstorm Survey (NASC...
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ftmdpi:oai:mdpi.com:/2072-4292/9/9/896/ 2023-08-20T03:59:11+02:00 North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) Louis Gonzalez Xavier Briottet agris 2017-08-30 application/pdf https://doi.org/10.3390/rs9090896 EN eng Multidisciplinary Digital Publishing Institute Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs9090896 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 9; Issue 9; Pages: 896 SEVIRI sandstorm day and night AOD retrieval North Africa Saudi Arabia Text 2017 ftmdpi https://doi.org/10.3390/rs9090896 2023-07-31T21:12:47Z The Meteosat Second Generation (MSG) geostationary platform equipped with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument provides observations of the Earth every 15 min since 2004. Based on those measurements, we present a new method called North African Sandstorm Survey (NASCube) to: (i) generate day/night remote sensing images in order to detect sandstorms over the Sahara and Saudi Arabia; and (ii) estimate day and night aerosol optical depth (AOD). This paper presents a method to create true color day and night images from the SEVIRI instrument level 1.5 products and the complete operational data processing system to detect sandstorms and quantify the AOD over the desert areas of North Africa and Saudi Arabia. The designed retrieval algorithms are essentially based on the use of artificial neural networks (ANN), which seems to be well suited to this issue. Our methods are validated against two different datasets, namely the Deep Blue NASA moderate-resolution imaging spectroradiometer (MODIS) product and AErosol RObotic NETwork (AERONET) acquisitions located in desert areas. It is shown that NASCube products deliver better estimations for high AOD (>0.2) over land areas than Deep Blue products. The open-public web platform will help researchers to identify, quantify and retrieve the impact of sandstorms over desert regions. Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 9 9 896 |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
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SEVIRI sandstorm day and night AOD retrieval North Africa Saudi Arabia |
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SEVIRI sandstorm day and night AOD retrieval North Africa Saudi Arabia Louis Gonzalez Xavier Briottet North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
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SEVIRI sandstorm day and night AOD retrieval North Africa Saudi Arabia |
description |
The Meteosat Second Generation (MSG) geostationary platform equipped with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument provides observations of the Earth every 15 min since 2004. Based on those measurements, we present a new method called North African Sandstorm Survey (NASCube) to: (i) generate day/night remote sensing images in order to detect sandstorms over the Sahara and Saudi Arabia; and (ii) estimate day and night aerosol optical depth (AOD). This paper presents a method to create true color day and night images from the SEVIRI instrument level 1.5 products and the complete operational data processing system to detect sandstorms and quantify the AOD over the desert areas of North Africa and Saudi Arabia. The designed retrieval algorithms are essentially based on the use of artificial neural networks (ANN), which seems to be well suited to this issue. Our methods are validated against two different datasets, namely the Deep Blue NASA moderate-resolution imaging spectroradiometer (MODIS) product and AErosol RObotic NETwork (AERONET) acquisitions located in desert areas. It is shown that NASCube products deliver better estimations for high AOD (>0.2) over land areas than Deep Blue products. The open-public web platform will help researchers to identify, quantify and retrieve the impact of sandstorms over desert regions. |
format |
Text |
author |
Louis Gonzalez Xavier Briottet |
author_facet |
Louis Gonzalez Xavier Briottet |
author_sort |
Louis Gonzalez |
title |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_short |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_full |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_fullStr |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_full_unstemmed |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_sort |
north africa and saudi arabia day/night sandstorm survey (nascube) |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2017 |
url |
https://doi.org/10.3390/rs9090896 |
op_coverage |
agris |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing; Volume 9; Issue 9; Pages: 896 |
op_relation |
Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs9090896 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs9090896 |
container_title |
Remote Sensing |
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9 |
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9 |
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896 |
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1774718159906930688 |